U.S. patent number 11,332,146 [Application Number 16/638,140] was granted by the patent office on 2022-05-17 for vehicle traveling control device, vehicle traveling control method, and program.
This patent grant is currently assigned to SONY CORPORATION. The grantee listed for this patent is Sony Corporation. Invention is credited to Suguru Aoki, Atsushi Ito, Hideki Oyaizu, Ryuta Satoh, Takeshi Uemori.
United States Patent |
11,332,146 |
Uemori , et al. |
May 17, 2022 |
Vehicle traveling control device, vehicle traveling control method,
and program
Abstract
An image captured by a far-infrared camera is analyzed to
analyze a distribution of a road-surface temperature, and a course
of a highest road-surface temperature is determined to be a
traveling route. Further, automatic driving along the course of the
highest road-surface temperature is performed. Furthermore, a state
of the distribution of a road-surface temperature, and a direction
of the course of the highest road-surface temperature are displayed
on a display section, so that a user (a driver) recognizes them.
For example, a state analyzer detects a candidate course travelable
for a vehicle, the state analyzer detecting a plurality of the
candidate courses, calculates an average value of a road-surface
temperature of each of the plurality of the candidate courses, and
determines the candidate course having a largest average value of a
road-surface temperature to be a traveling route.
Inventors: |
Uemori; Takeshi (Tokyo,
JP), Ito; Atsushi (Kanagawa, JP), Oyaizu;
Hideki (Tokyo, JP), Aoki; Suguru (Tokyo,
JP), Satoh; Ryuta (Kanagawa, JP) |
Applicant: |
Name |
City |
State |
Country |
Type |
Sony Corporation |
Tokyo |
N/A |
JP |
|
|
Assignee: |
SONY CORPORATION (Tokyo,
JP)
|
Family
ID: |
1000006314197 |
Appl.
No.: |
16/638,140 |
Filed: |
July 13, 2018 |
PCT
Filed: |
July 13, 2018 |
PCT No.: |
PCT/JP2018/026525 |
371(c)(1),(2),(4) Date: |
February 11, 2020 |
PCT
Pub. No.: |
WO2019/035300 |
PCT
Pub. Date: |
February 21, 2019 |
Prior Publication Data
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|
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Document
Identifier |
Publication Date |
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US 20200172110 A1 |
Jun 4, 2020 |
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Foreign Application Priority Data
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Aug 18, 2017 [JP] |
|
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JP2017-157820 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B60W
60/001 (20200201); G01C 21/3697 (20130101); B60W
40/068 (20130101); G01J 5/10 (20130101); B60W
2554/00 (20200201); G01J 5/485 (20220101); B60W
2520/10 (20130101); B60W 2420/42 (20130101); G01J
2005/0077 (20130101); B60W 2420/40 (20130101); B60W
2552/40 (20200201) |
Current International
Class: |
G01N
25/72 (20060101); G01J 5/10 (20060101); B60W
40/068 (20120101); B60W 60/00 (20200101); G01C
21/36 (20060101); G01J 5/00 (20220101) |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
|
|
|
|
|
|
|
101363737 |
|
Feb 2009 |
|
CN |
|
103164962 |
|
Jun 2013 |
|
CN |
|
203364978 |
|
Dec 2013 |
|
CN |
|
105252973 |
|
Jan 2016 |
|
CN |
|
1020131797 |
|
Jun 2015 |
|
DE |
|
2765046 |
|
Aug 2014 |
|
EP |
|
05-016623 |
|
Jan 1993 |
|
JP |
|
2003176519 |
|
Jun 2003 |
|
JP |
|
2010-115100 |
|
May 2010 |
|
JP |
|
2010-163131 |
|
Jul 2010 |
|
JP |
|
2012-101762 |
|
May 2012 |
|
JP |
|
2012-230067 |
|
Nov 2012 |
|
JP |
|
103413441 |
|
Nov 2013 |
|
JP |
|
2016-075503 |
|
May 2016 |
|
JP |
|
2016-162172 |
|
Sep 2016 |
|
JP |
|
2016-162172 |
|
Sep 2016 |
|
JP |
|
Other References
International Search Report and Written Opinion dated Sep. 18, 2018
for PCT/JP2018/026525 filed on Jul. 13, 2018, 8 pages including
English Translation of the International Search Report. cited by
applicant .
"Road surface area detection from in-vehicle camera image by Random
Forest," 24 pages. cited by applicant .
Yohei Mishina, et al., "Road surface area detection from in-vehicle
camera image by Random Forest," 19th Symposium on Sensing via
Imaging Information, Yokohama, Jun. 2013, 24 pages. cited by
applicant.
|
Primary Examiner: Kan; Yuri
Attorney, Agent or Firm: Xsensus LLP
Claims
The invention claimed is:
1. A vehicle traveling control device comprising: circuitry
configured to acquire an image of a region situated in a travel
direction of a vehicle, the image being captured by a far-infrared
camera to analyze a distribution of a road-surface temperature;
detect two or more candidate courses of the vehicle to be safely
travelable based on vehicle state information of the vehicle and
surrounding information of the vehicle acquired by a sensor, the
state vehicle state information including at least one of a
location of the vehicle, a pose of the vehicle, and movement of the
vehicle, and the surrounding information of the vehicle including
at least one of a type, a location, and movement of an obstacle
object around the vehicle; and determine a course of a highest
road-surface temperature to be a traveling route, based on the
distribution of a road-surface temperature, the course being
determined from the two or more candidate courses of the
vehicle.
2. The vehicle traveling control device according to claim 1,
wherein the circuitry is further configured to perform automatic
driving of hg vehicle, the vehicle being guided to travel along the
course of the highest road-surface temperature.
3. The vehicle traveling control device according to claim 1,
wherein the circuitry is further configured to calculate an average
value of the road-surface temperature of each of the plurality of
the candidate courses, and determine, to be the traveling route,
the candidate course having a largest average value of the
road-surface temperature.
4. The vehicle traveling control device according to claim 1,
wherein the circuitry is further configured to calculate a maximum
value or a median value of the road-surface temperature of each of
the plurality of the candidate courses, and determine, to be the
traveling route, the candidate course having a largest maximum
value or a largest median value of the road-surface
temperature.
5. The vehicle traveling control device according to claim 3,
wherein the circuitry is further configured to determine the
candidate courses which is travelable in the travel direction of
the vehicle without sharp change in course from a current traveling
course.
6. The vehicle traveling control device according to claim 1,
wherein the circuitry is further configured to extract a
road-surface region from the image of the region situated in the
travel direction of the vehicle, the image being captured by a
visible light camera, and analyze the distribution of the
temperature of the road surface included in the extracted
road-surface region.
7. The vehicle traveling control device according to claim 1,
further comprising a display that displays direction information
regarding the course of the highest road-surface temperature.
8. The vehicle traveling control device according to claim 7,
wherein the display displays information indicating a temperature
distribution of a road-surface temperature.
9. The vehicle traveling control device according to claim 8,
wherein the display displays, as the information indicating a
temperature distribution of a road-surface temperature, information
in which an output color depending on a temperature is set.
10. A vehicle traveling control method that is performed in a
vehicle traveling control device, the method comprising: acquiring,
by a far-infrared camera, an image of a region situated in a travel
direction of a vehicle, to analyze a distribution of a road-surface
temperature; detecting, by a sensor, two or more candidate courses
of the vehicle to be safely travelable based on vehicle state
information of the vehicle and surrounding information of the
vehicle acquired by a sensor, the state vehicle state information
including at least one of a location of the vehicle, a pose of the
vehicle, and movement of the vehicle, and the surrounding
information of the vehicle including at least one of a type, a
location, and movement of an obstacle object around the vehicle;
and determining a course of a highest road-surface temperature to
be a traveling route, based on the distribution of a road-surface
temperature, the course being determined from the two or more
candidate courses of the vehicle.
11. A non-transitory computer-readable storage medium including
computer executable instructions, wherein the instructions, when
executed by a vehicle traveling control device, cause the vehicle
traveling control device to perform a method, the method
comprising: acquiring, by a far-infrared camera, an image of a
region situated in a travel direction of a vehicle, to analyze a
distribution of a road-surface temperature; detecting, by a sensor,
two or more candidate courses of the vehicle to be safely
travelable based on vehicle state information of the vehicle and
surrounding information of the vehicle acquired by a sensor, the
state vehicle state information including at least one of a
location of the vehicle, a pose of the vehicle, and movement of the
vehicle, and the surrounding information of the vehicle including
at least one of a type, a location, and movement of an obstacle
object around the vehicle; and determining a course of a highest
road-surface temperature to be a traveling route, based on the
distribution of a road-surface temperature, the course being
determined from the two or more candidate courses of the
vehicle.
12. The vehicle traveling control device according to claim 1,
wherein the sensor includes at least one of an image-capturing
device such as a time-of-flight (ToF) camera, a visible light
camera, a stereo camera, a monocular camera, an environment sensor
for detecting a weather condition, and a surroundings-information
detection sensor for detecting the obstacle object around the
vehicle.
13. The vehicle traveling control device according to claim 12,
wherein the environment sensor for detecting the weather condition
includes at least one of a raindrop sensor, a fog sensor, a
sunlight sensor, and a snow sensor.
14. The vehicle traveling control device according to claim 12,
wherein the surroundings-information detection sensor for detecting
the obstacle object around the vehicle includes at least one of an
ultrasonic sensor, a radar, LiDAR (light detection and ranging,
laser imaging detection and ranging), and a sonar.
15. The vehicle traveling control device according to claim 14,
wherein the surroundings-information detection sensor is configured
to detect, as the obstacle object around the vehicle, at least one
of other vehicle, a human being, a structure, a road, a traffic
light, a traffic sign, and a road sign.
16. The vehicle traveling control device according to claim 12,
wherein the sensor includes a global navigation satellite system
(GNSS) receiver that receives a GNSS signal from a GNSS satellite
to detect a current location of the vehicle.
17. The vehicle traveling control device according to claim 1,
wherein the circuitry is further configured to analyze a location
and a state of a traffic light around the vehicle, a traffic
regulation around the vehicle, and a travelable lane, based on
information acquired by the sensor.
18. The vehicle traveling control device according to claim 2,
wherein the circuitry is further configured to perform the
automatic driving which is a cooperative control in order to
provide a function of an advanced driver assistance system (ADAS)
including at least one of collision avoidance, impact relaxation of
the vehicle, traveling after a leading vehicle based on a distance
between the vehicles, traveling while maintaining a vehicle speed
of the vehicle, a warning of a collision of the vehicle, and a
warning of deviation of the vehicle from a predetermined lane.
19. The vehicle traveling control device according to claim 18,
wherein the circuitry is further configured to perform the
cooperative control in order to the achieve automatic driving which
is to drive the vehicle autonomously without an operation performed
by a driver of the vehicle.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
The present application is based on PCT filing PCT/JP2018/026525,
filed Jul. 13, 2018, which claims priority to JP 2017-157820, filed
Aug. 18, 2017, the entire contents of each are incorporated herein
by reference.
TECHNICAL FIELD
The present disclosure relates to a vehicle traveling control
device, a vehicle traveling control method, and a program. In
particular, the present disclosure relates to a vehicle traveling
control device, a vehicle traveling control method, and a program
that achieve an improvement in fuel efficiency when a vehicle is
traveling.
BACKGROUND ART
It is known that there is a correlation between a tire temperature
and fuel efficiency when an automobile is traveling.
For example, Patent Literature 1 (Japanese Patent Application
Laid-open No. 2016-075503) discloses an evaluation device that
measures a relationship between a temperature and a rolling
resistance of a tire.
Further, Patent Literature 2 (Japanese Patent Application Laid-open
No. 2012-101762) discloses a device that calculates a rolling
resistance of a tire using a tire temperature detected by detection
means provided in a vehicle, calculates energy consumption using a
travel distance of an automobile on a route from a departure point
to a destination, and the calculated rolling distance, and presents
the calculated energy consumption to a driver.
CITATION LIST
Patent Literature
Patent Literature 1: Japanese Patent Application Laid-open No.
2016-075503
Patent Literature 2: Japanese Patent Application Laid-open No.
2012-101762
Non-Patent Literature
Non-Patent Literature 1:
http://www.vision.cs.chubu.ac.jp/MPRG/f_group/f133_mishina2013.pdf
DISCLOSURE OF INVENTION
Technical Problem
The technologies disclosed in the two patent literatures described
above both measure a temperature of a tire itself and estimate a
rolling resistance and the fuel efficiency from the temperature of
the tire.
However, no other patent literatures including the patent
literatures described above disclose measuring a road temperature,
estimating the fuel efficiency, and controlling a vehicle.
It is conceivable that the tire temperature is greatly affected by
a temperature of a road surface during traveling and is changed
according to the temperature of a road, and the fuel efficiency
varies due to the change in the tire temperature.
An object of the present disclosure is to provide a vehicle
traveling control device, a vehicle traveling control method, and a
program that achieve a vehicle traveling control with improved fuel
efficiency, the vehicle traveling control including measuring a
distribution of a temperature of a road in a travel direction of a
traveling vehicle, estimating a traveling route with less fuel
consumption, and controlling a vehicle traveling route.
Solution to Problem
A vehicle traveling control device according to a first aspect of
the present disclosure includes
a detector that analyzes an image captured by a far-infrared camera
to analyze a distribution of a road-surface temperature; and
a state analyzer that determines a course of a highest road-surface
temperature to be a traveling route, using the distribution of a
road-surface temperature.
Further, a vehicle traveling control method according to a second
aspect of the present disclosure is performed in a vehicle
traveling control device, and includes
performing, by a detector, detection including analyzing an image
captured by a far-infrared camera to analyze a distribution of a
road-surface temperature; and
performing, by a state analyzer, a state analysis including
determining a course of a highest road-surface temperature to be a
traveling route, using the distribution of a road-surface
temperature.
Furthermore, a program according to a third aspect of the present
disclosure causes a vehicle traveling control device to perform a
vehicle traveling control, the vehicle traveling control
including
performing detection including causing a detector to analyze an
image captured by a far-infrared camera to analyze a distribution
of a road-surface temperature; and
performing a state analysis including causing a state analyzer to
determine a course of a highest road-surface temperature to be a
traveling route, using the distribution of a road-surface
temperature.
Note that the program of the present disclosure is, for example, a
program that can be provided to an information processing device or
a computer system by a recording medium or a communication medium,
the information processing device or the computer system being
capable of executing various program codes, the recording medium or
the communication medium providing a program in a computer-readable
form. By such a program being provided in a computer-readable form,
a process depending on a program is performed on an information
processing device or a computer system.
The other objects, features, and advantages of the present
disclosure will be apparent from more detailed descriptions based
on embodiments of the present disclosure described later and the
appended drawings. Note that a system herein is a logical
collection of a plurality of devices, and is not limited to having
a configuration in which each included device is situated in a
single housing.
Advantageous Effects of Invention
The configuration of an embodiment of the present disclosure makes
it possible to travel while detecting a road-surface temperature
and selecting a region of a high road-surface temperature, and thus
to travel with improved fuel efficiency.
Specifically, for example, an image captured by a far-infrared
camera is analyzed to analyze a distribution of a road-surface
temperature, and a course of a highest road-surface temperature is
determined to be a traveling route. Further, automatic driving
along the course of the highest road-surface temperature is
performed. Furthermore, a state of the distribution of a
road-surface temperature, and a direction of the course of the
highest road-surface temperature are displayed on a display
section, so that a user (a driver) recognizes them. For example, a
state analyzer detects a candidate course travelable for a vehicle,
the state analyzer detecting a plurality of the candidate courses,
calculates an average value of a road-surface temperature of each
of the plurality of the candidate courses, and determines the
candidate course having a largest average value of a road-surface
temperature to be a traveling route.
This configuration makes it possible to travel while detecting a
road-surface temperature and selecting a region of a high
road-surface temperature, and thus to travel with improved fuel
efficiency.
Note that the effect disclosed herein is merely illustrative but is
not limitative, and any additional effect may be provided.
BRIEF DESCRIPTION OF DRAWINGS
FIG. 1 illustrates an outline of a process performed by a vehicle
traveling control device of the present disclosure.
FIG. 2 is a diagram explaining a visible light image and a
far-infrared image.
FIG. 3 is a graph illustrating a correspondence relationship
between a tire temperature and a rolling resistance
coefficient.
FIG. 4 illustrates an outline of a process performed by the vehicle
traveling control device of the present disclosure.
FIG. 5 illustrates an outline of a process performed by the vehicle
traveling control device of the present disclosure.
FIG. 6 is a diagram of an example of a configuration of the vehicle
traveling control device of the present disclosure.
FIG. 7 is a flowchart of a sequence of a process performed by the
vehicle traveling control device of the present disclosure.
FIG. 8 is a diagram explaining the process performed by the vehicle
traveling control device of the present disclosure and an example
of a display on a display section.
FIG. 9 is a diagram explaining the process performed by the vehicle
traveling control device of the present disclosure and an example
of a display on the display section.
FIG. 10 is a diagram explaining the process performed by the
vehicle traveling control device of the present disclosure and an
example of a display on the display section.
FIG. 11 is a diagram explaining the process performed by the
vehicle traveling control device of the present disclosure and an
example of a display on the display section.
MODE(S) FOR CARRYING OUT THE INVENTION
A vehicle traveling control device, a vehicle traveling control
method, and a program will now be described in detail with
reference to the drawings. Note that the descriptions are made in
accordance with the following items.
1. Outline of Process Performed by Vehicle Traveling Control
Device
2. Example of Configuration of Vehicle Traveling Control Device
3. Sequence of Process Performed by Vehicle
Traveling Control Device
4. Summary of Configuration of Present Disclosure
1. Outline of Process Performed by Vehicle Traveling Control
Device
First, an outline of a process performed by the vehicle traveling
control device of the present disclosure is described with
reference to FIG. 1 and figures subsequent to FIG. 1.
FIG. 1 illustrates an example of a process performed by the vehicle
traveling control device of the present disclosure.
The vehicle traveling control device of the present disclosure is
provided in an automobile 10 illustrated in FIG. 1. A far-infrared
camera 20 is provided in a front portion of the automobile 10, and
captures a far-infrared image of a front region situated in a
travel direction of the automobile 10.
The far-infrared camera 20 is a camera that captures an image of
far-infrared radiation having a longer wavelength from among
infrared radiation.
More infrared radiation is emitted from an object of a higher
temperature. Thus, infrared radiation makes it possible to, for
example, detect a high-temperature object such as a human being in,
for example, the darkness, and is often used in, for example, a
surveillance camera.
From among infrared radiation, far-infrared radiation is more
highly sensitive to heat, so it is possible to find out a
high-temperature portion and a low-temperature portion using a
far-infrared image.
The far-infrared image is, for example, a light-and-shade image
depending on a temperature distribution. Specifically, it is a
monochrome image that becomes whiter with a higher temperature, in
which, for example, a high-temperature portion is represented in
white and a low-temperature portion is represented in black.
An example of a wavelength of which an image is captured as a
visible light image or a far-infrared image, is described, with
reference to FIG. 2.
As illustrated in FIG. 2, a visible light image 30 is an image in
which the wavelength is in a range of about 0.4 .mu.m to 0.7 .mu.m,
and is a color image such as an RGB image that is captured using a
commonly used camera.
The infrared light image is an image of light of a long wavelength
in which the wavelength is 0.7 .mu.m or more. An
infrared-light-image capturing camera that captures an
infrared-light image is capable of capturing an image of an object
that produces heat, such as a human being, as described above, and
is used in, for example, a surveillance camera.
As illustrated in FIG. 2, infrared radiation is classified as
below:
near-infrared radiation in which the wavelength is about 0.7 to 1
.mu.m,
mid-infrared radiation in which the wavelength is about 3 to 5
.mu.m, and
far-infrared radiation in which the wavelength is about 8 to 14
.mu.m.
As described above, far-infrared radiation is highly sensitive to
heat, so it is possible to easily find out a high-temperature
portion and a low-temperature portion using a far-infrared
image.
In embodiments described below, an example of image processing
performed using a far-infrared image 40 obtained by performing
image-capturing on far-infrared radiation in which the wavelength
is primarily about 8 to 14 .mu.m, is described.
However, the processing of the present disclosure is not limited to
being performed using a far-infrared image, and other infrared
light images can also be used.
Referring back to FIG. 1, an example of a process performed by the
vehicle traveling control device of the present disclosure is
described.
The far-infrared camera 20 provided in the front portion of the
automobile 10 illustrated in FIG. 1 continuously captures a
far-infrared image of a preceding road in the travel direction of
the automobile 10.
As described above, the analysis of a far-infrared image of a
subject that is captured by the far-infrared camera 20 makes it
possible to analyze a distribution of a temperature of the subject
of the captured image.
The vehicle traveling control device of the present disclosure
analyzes a far-infrared image of a road that is captured by the
far-infrared camera 20, so as to analyze a distribution of a
temperature of the road of the captured image.
For example, the automobile 10 is traveling in a left lane on a
two-lane road, as illustrated in FIG. 1.
The far-infrared camera 20 consecutively captures a far-infrared
image of the entirety of a portion of the road in width that is
travelable for the automobile 10, from the left lane to a right
lane. For example, the far-infrared camera 20 captures far-infrared
images as a moving image.
The vehicle traveling control device analyzes a far-infrared image
of the road that is captured by the far-infrared camera 20, and,
for example, as illustrated in FIG. 1, the vehicle traveling
control device analyzes a distribution of a temperature of the road
of the captured image.
For example, the analysis result illustrated in FIG. 1 can be
obtained. In other words, a distribution of a temperature of the
road for each region can be obtained as indicated below, as
illustrated in FIG. 1:
the left-lane region in which the automobile 10 is traveling, is a
high-temperature region,
the middle region between the left lane and the right lane
(lane-indicating-line region) is a low-temperature region, and
the right lane is a medium-temperature region.
Using the temperature analysis result, the vehicle traveling
control device determines a route of a highest road-surface
temperature to be a route providing the best fuel efficiency, and
thus to be a traveling route. The vehicle traveling control device
controls traveling of the automobile 10 according to the determined
traveling route.
Note that FIG. 1 illustrates an example of an automobile
automatically steered in an automatic driving mode.
In the example illustrated in FIG. 1, the left-lane region in which
the automobile 10 is now traveling is a high-temperature region.
The tire temperature is kept at a high temperature by the
automobile 10 keeping on traveling in the left-lane region, and
thus it becomes possible to travel with a reduced rolling
resistance. This results in being able to travel with good fuel
efficiency.
Note that a relationship between a tire temperature and a
coefficient of a rolling resistance of the tire is already known,
and, for example, there is a relationship that follows the graph
illustrated in FIG. 3.
FIG. 3 is a graph having a tire temperature on its horizontal axis
and a coefficient (.mu.) of a rolling resistance of the tire on its
vertical axis.
As can be seen from the graph illustrated in FIG. 3, the rolling
resistance coefficient (.mu.) is smaller if the tire temperature is
higher.
The rolling resistance (R) of a tire can be calculated using a
formula indicated below (Formula 1) by use of the rolling
resistance coefficient (.mu.). R=.mu.mg (Formula 1)
Note that, in Formula 1 described above, p represents a coefficient
of a rolling resistance of a tire, m represents a vehicle weight,
and g represents gravitational acceleration.
As can be seen from Formula 1 described above, the rolling
resistance (R) of a tire is smaller if the rolling resistance
coefficient (.mu.) is smaller.
Further, as indicated by the graph illustrated in FIG. 3, the
coefficient (.mu.) of a rolling resistance is smaller if the
temperature is higher. Thus, in an automobile, it is possible to
make the rolling resistance (R) of a tire smaller if the tire
temperature is higher, which results in being able to travel with
good fuel efficiency.
In the example illustrated in FIG. 1, the road surface of the
left-lane region in which the automobile 10 is now traveling is a
high-temperature region. The tire temperature is kept at a high
temperature by the automobile 10 keeping on traveling in the
left-lane region, and thus it becomes possible to travel with a
reduced rolling resistance. This results in achieving traveling
with good fuel efficiency.
Using the temperature analysis result, the vehicle traveling
control device determines that the left-lane region is a
high-temperature region and thus is a route providing the best fuel
efficiency, selects the left lane to be a traveling route, and
controls traveling of the automobile 10 in accordance with a result
of the selection, such that the automobile 10 is set in the left
lane.
Note that capturing of a far-infrared image performed by the
far-infrared camera 20, and an analysis of a distribution of a
temperature of a road surface for each region are continuously
performed.
Thus, a result of analyzing a temperature distribution using a
captured far-infrared image is also successively updated.
For example, it is assumed that the result of analyzing a
temperature distribution using a far-infrared image is changed to
the state illustrated in FIG. 4 while the automobile 10 is
traveling in the left lane according to the temperature analysis
result illustrated in FIG. 1.
FIG. 4 illustrates an example of the result of analyzing a
temperature distribution using a far-infrared image, where
the left-lane region in which the automobile 10 is traveling, is a
medium-temperature region,
the middle region between the left lane and the right lane
(lane-indicating-line region) is a low-temperature region, and
the right lane is a high-temperature region.
When the temperature distribution for each road region illustrated
in FIG. 4 is obtained as a result of analyzing a temperature
distribution using a far-infrared image, the vehicle traveling
control device of the automobile 10 performs a process
including:
determining, using the temperature analysis result, that a region
of the right lane is a high-temperature region and thus is a route
providing the best fuel efficiency; selecting the right lane to be
a traveling route; and performing a traveling control to move the
automobile 10 to the right lane in accordance with a result of the
selection.
Note that a lane change is made after distances to vehicles
traveling ahead and behind are checked to confirm that there are
safe distances between vehicles.
The configuration described in reference to FIGS. 1 and 4 is an
example of providing the vehicle traveling control device of the
present disclosure in an automobile that is capable of traveling in
an automatic driving mode.
The vehicle traveling control device of the present disclosure can
be provided not only in such an automobile that is capable of
traveling in an automatic driving mode, but also in an automobile
that does not include a function of an automatic driving mode.
An example of a process performed by the vehicle traveling control
device of the present disclosure when the vehicle traveling control
device is provided in an automobile that does not include a
function of an automatic driving mode, is described with reference
to FIG. 5.
FIG. 5 illustrates an example of a process performed by the vehicle
traveling control device of the present disclosure, as in the case
of FIG. 1.
The vehicle traveling control device of the present disclosure is
provided in the automobile 10 illustrated in FIG. 5. The
far-infrared camera 20 is provided in the front portion of the
automobile 10, and captures a far-infrared image of a front region
situated in the travel direction of the automobile 10.
The vehicle traveling control device provided in the automobile 10
analyzes a far-infrared image of a road that is captured by the
far-infrared camera 20.
The vehicle traveling control device of the automobile 10
illustrated in FIG. 5 displays a result of analyzing the
far-infrared image on a display section 50 that is included in the
automobile.
As illustrated in FIG. 5, the following information regarding a
temperature distribution for each road region is displayed on the
display section 50:
the left-lane region in which the automobile 10 is traveling, is a
high-temperature region,
the middle region between the left lane and the right lane
(lane-indicating-line region) is a low-temperature region, and
the right lane is a medium-temperature region.
The vehicle traveling control device of the automobile 10
illustrated in FIG. 5 acquires such information regarding a
temperature distribution for each road region, and displays the
acquired information on the display section 50.
Note that an output color depending on a temperature may be set to
perform display on the display section 50.
As illustrated in FIG. 5,
the high-temperature region that is the left-lane region in which
the automobile 10 is traveling, is output in a red-color
setting,
the low-temperature region that is the middle region between the
left lane and the right lane (lane-indicating-line region), is
output in a green-color setting, and
the medium-temperature region that is the right lane is output in a
yellow-color setting.
Such color-coding upon performing outputting enables a user (a
driver) to know a road-surface temperature immediately.
The vehicle traveling control device of the automobile 10
illustrated in FIG. 5 further selects, using the temperature
analysis result, a route providing the best fuel efficiency to be a
traveling route, and displays recommended-route information 52 on
the display section 50 of the automobile 10 in accordance with a
result of the selection.
In the example illustrated in the figure, the left-lane region in
which the automobile 10 is traveling, is a high-temperature region,
and an arrow that indicates a travel direction in the left lane is
displayed as the recommended-route information 52.
A driver of the automobile 10 can select a high-temperature region
of a road to travel on the high-temperature region, by steering the
automobile 10 in accordance with the information displayed on the
display section 50, that is, the recommended-route information
52.
Such a traveling process makes it possible to travel with good fuel
efficiency.
Note that, also with respect to the automobile including a function
of an automatic driving mode described with reference to FIGS. 1
and 4, a setting may be performed such that a state of a
distribution of a road temperature and recommended-route
information similar to those illustrated in FIG. 5, are displayed
on a display section of the automobile while selecting a
high-temperature region of the road and performing automatic
driving.
The display of information while performing automatic driving
enables a driver to know, in advance, that an automobile travels
along a recommended route displayed on a display section, and to
know, in advance, that there may be a change in, for example, a
lane for traveling.
2. Example of Configuration of Vehicle Traveling Control Device
Next, an example of a configuration of the vehicle traveling
control device is described with reference to FIG. 6.
FIG. 6 is a block diagram of an example of a schematic functional
configuration of a vehicle control system 100 that is an example of
the vehicle traveling control device that is included in the
automobile 10 and performs the process described above.
Note that, when a vehicle provided with the vehicle control system
100 is to be distinguished from other vehicles, it will be
hereinafter referred to as a system-installed automobile or a
system-installed vehicle.
The vehicle control system 100 includes an input section 101, a
data acquisition section 102, a communication section 103, an
in-vehicle device 104, an output controller 105, an output section
106, a driveline controller 107, a driveline system 108, a
body-related controller 109, a body-related system 110, a storage
111, and an automatic driving controller 112. The input section
101, the data acquisition section 102, the communication section
103, the output controller 105, the driveline controller 107, the
body-related controller 109, the storage 111, and the automatic
driving controller 112 are connected to one another through a
communication network 121. Examples of the communication network
121 include an onboard communication network and a bus that meet
any standard such as a controller area network (CAN), a local
interconnect network (LIN), a local area network (LAN), and FlexRay
(registered trademark). Note that the respective components of the
vehicle control system 100 may also be directly connected to one
another without the communication network 121.
Note that the description of the communication network 121 will be
omitted below when the respective components of the vehicle control
system 100 communicate with one another through the communication
network 121. For example, when the input section 101 and the
automatic driving controller 112 communicate with each other
through the communication network 121, it will be simply stated
that the input section 101 and the automatic driving controller 112
communicate with each other.
The input section 101 includes a device used by a person on board
to input, for example, various data and instructions. For example,
the input section 101 includes a manipulation device such as a
touch panel, a button, microphones, a switch, and a lever, as well
as a manipulation device on which input can be performed by a
method other than a manual manipulation, such as sound or a
gesture. Further, for example, the input section 101 may be an
externally connected device such as a remote-control device that
uses infrared or other radio waves, or a mobile device or a
wearable device that can deal with manipulating the vehicle control
system 100. The input section 101 generates an input signal
according to data or an instruction input by a person on board, and
provides the input signal to each component of the vehicle control
system 100.
The data acquisition section 102 includes, for example, various
sensors that acquire data used for a process performed by the
vehicle control system 100, and provides the acquired data to each
component of the vehicle control system 100.
For example, the data acquisition section 102 includes various
sensors for detecting, for example, a state of the system-installed
automobile. Specifically, for example, the data acquisition section
102 includes, for example, a gyroscope, an acceleration sensor, an
inertial measurement unit (IMU), and a sensor for detecting, for
example, an amount of operating a gas pedal, an amount of operating
a brake pedal, a steering angle for a steering wheel, the number of
engine rotation, the number of motor rotation, or a speed of wheel
rotation.
Further, for example, the data acquisition section 102 includes
various sensors for detecting information regarding the outside of
the system-installed automobile. Specifically, for example, the
data acquisition section 102 includes an image-capturing device
such as a time-of-flight (ToF) camera, a visible light camera, a
stereo camera, a monocular camera, a (far-)infrared camera, and
other cameras. Furthermore, for example, the data acquisition
section 102 includes an environment sensor for detecting, for
example, weather or a weather condition, and a
surroundings-information detection sensor for detecting an object
around the system-installed automobile. Examples of the environment
sensor include a raindrop sensor, a fog sensor, a sunlight sensor,
and a snow sensor. Examples of the surroundings-information
detection sensor include an ultrasonic sensor, a radar, LiDAR
(light detection and ranging, laser imaging detection and ranging),
and a sonar.
Moreover, for example, the data acquisition section 102 includes
various sensors for detecting a current location of the
system-installed automobile. Specifically, for example, the data
acquisition section 102 includes, for example, a global navigation
satellite system (GNSS) receiver that receives a GNSS signal from a
GNSS satellite.
Further, for example, the data acquisition section 102 includes
various sensors for detecting in-vehicle information. Specifically,
for example, the data acquisition section 102 includes, for
example, an image-capturing device that captures an image of a
driver, a biological sensor that detects biological information
regarding a driver, and microphones that collect sound inside a
vehicle. The biological sensor is provided in, for example, a
seating surface or a steering wheel, and detects biological
information regarding a person on board who is sitting on a seat,
or a driver behind the steering wheel.
The communication section 103 communicates with the in-vehicle
device 104 as well as various vehicle-exterior devices, servers,
base stations, and the like, and transmits data provided by each
component of the vehicle control system 100 and provides received
data to each component of the vehicle control system 100. Note that
the communication protocol supported by the communication section
103 is not particularly limited, and the communication section 103
may also support a plurality of types of communication
protocols.
For example, the communication section 103 wirelessly communicates
with the in-vehicle device 104 using, for example, a wireless LAN,
Bluetooth (registered trademark), near field communication (NFC),
or a wireless USB (WUSB). Further, for example, the communication
section 103 communicates with the in-vehicle device 104 by wire
using, for example, a universal serial bus (USB), a high-definition
multimedia interface (HDMI) (registered trademark), or a mobile
high-definition link (MHL) through a connection terminal (not
illustrated) (and a cable if necessary).
Further, for example, the communication section 103 communicates
with a device (such as an application server or a control server)
situated in an external network (such as the Internet, a cloud
network, or a carrier-specific network) through a base station or
an access point. Furthermore, for example, the communication
section 103 communicates with a terminal situated near the
system-installed automobile (such as a terminal of a pedestrian or
a store, or a machine-type-communication (MTC) terminal), using a
peer to peer (P2P) technology. Moreover, for example, the
communication section 103 performs a V2X communication such as a
vehicle-to-vehicle communication, a vehicle-to-infrastructure
communication, a vehicle-to-home communication between the
system-installed automobile and a home, and a vehicle-to-pedestrian
communication. Further, for example, the communication section 103
includes a beacon receiver, receives a radio wave or an
electromagnetic wave transmitted by, for example, a wireless
station placed on a road, and acquires information regarding, for
example, a current location, a traffic jam, a traffic regulation,
or a necessary time.
Examples of the in-vehicle device 104 include a mobile device or a
wearable device of a person on board, an information device that is
brought in or provided in the system-installed automobile, and a
navigation device that searches for a route to any destination.
The output controller 105 controls outputs of various pieces of
information to a person on board of the system-installed automobile
or to the outside of the system-installed automobile. For example,
the output controller 105 controls outputs of visual information
(such as image data) and auditory information (such as sound data)
from the output section 106 by generating an output signal that
includes at least one of the visual information or the auditory
information and providing the output signal to the output section
106. Specifically, for example, the output controller 105 combines
pieces of data of images respectively captured by different
image-capturing devices of the data acquisition section 102,
generates, for example, a long-shot image or a panoramic image, and
provides an output signal that includes the generated image to the
output section 106. Further, for example, the output controller 105
generates sound data that includes, for example, a warning beep or
a warning message alerting a danger such as collision, contact, or
an entry into a dangerous zone, and provides an output signal that
includes the generated sound data to the output section 106.
The output section 106 includes a device that is capable of
outputting visual information or auditory information to a person
on board of the system-installed automobile or to the outside of
the system-installed automobile. For example, the output section
106 includes, for example, a display device, an instrument panel,
an audio speaker, headphones, a wearable device such as an
eyeglass-style display that is used to be worn on a person on
board, a projector, and a lamp. In addition to a display device
that includes a commonly used display, the display device included
in the output section 106 may be a device, such as a head-up
display, a transmissive display, or a device including an augmented
reality (AR) display function, that displays visual information in
the field of view of a driver.
The driveline controller 107 controls the driveline system 108 by
generating various control signals and providing them to the
driveline system 108. Further, the driveline controller 107
provides a control signal to the respective components other than
the driveline system 108 as necessary to, for example, report a
state of controlling the driveline system 108.
The driveline system 108 includes various devices related to a
driveline of the system-installed automobile. For example, the
driveline system 108 includes, for example, a drive force
generator, such as an internal-combustion engine and a driving
motor, that generates a drive force, a drive force transmission
mechanism for transmitting a drive force to wheels, a steering
mechanism that performs rudder adjustment, a braking device that
generates a braking force, an antilock brake system (ABS), an
electronic stability control (ESC), and an electric power steering
device.
The body-related controller 109 controls the body-related system
110 by generating various control signals and providing them to the
body-related system 110. Further, the body-related controller 109
provides a control signal to the respective components other than
the body-related system 110 as necessary to, for example, report a
state of controlling the body-related system 110.
The body-related system 110 includes various body-related devices
included in a vehicle body. For example, the body-related system
110 includes, for example, a keyless entry system, a smart key
system, a power window device, a power seat, a steering wheel, an
air conditioner, and various lamps (such as a headlamp, a back
lamp, a stop lamp, a blinker, and a fog lamp).
The storage 111 includes, for example, a magnetic-storage device
such as a read only memory (ROM), a random access memory (RAM), and
a hard disc drive (HDD), a semiconductor storage device, an optical
storage device, and a magneto-optical storage device. The storage
111 stores therein various programs and data used by the respective
components of the vehicle control system 100. For example, the
storage 111 stores therein map data such as a three-dimensional
high-precision map such as a dynamic map, a global map that is less
precise and covers a wider area than a high-precision map, and a
local map that includes information regarding the surroundings of
the system-installed automobile.
The automatic driving controller 112 performs a control related to
automatic driving such as autonomous traveling and a driving
assistance. Specifically, for example, the automatic driving
controller 112 performs a cooperative control in order to provide a
function of an advanced driver assistance system (ADAS) including,
for example, collision avoidance or impact relaxation of the
system-installed automobile, traveling after a leading vehicle
based on a distance between vehicles, traveling while maintaining a
vehicle speed, a warning of a collision of the system-installed
automobile, or a warning of deviation of the system-installed
automobile from a lane. Further, for example, the automatic driving
controller 112 performs a cooperative control in order to achieve,
for example, automatic driving that is to travel autonomously
without an operation performed by a driver. The automatic driving
controller 112 includes a detector 131, a self-location estimator
132, a state analyzer 133, a planning section 134, and an operation
controller 135.
The detector 131 detects various pieces of information necessary to
control automatic driving. The detector 131 includes a
vehicle-exterior information detector 141, an in-vehicle
information detector 142, and a vehicle state detector 143.
The vehicle-exterior information detector 141 performs a process of
detecting information regarding the outside of the system-installed
automobile using data or a signal from each component of the
vehicle control system 100. For example, the vehicle-exterior
information detector 141 performs processes of detecting,
recognizing, and tracking an object around the system-installed
automobile, and a process of detecting a distance to the object.
Examples of the detection-target object include a vehicle, a human
being, an obstacle, a structure, a road, a traffic light, a traffic
sign, and a road sign. Further, for example, the vehicle-exterior
information detector 141 performs a process of detecting an
environment surrounding the system-installed automobile. Examples
of the detection-target surrounding environment include weather,
temperature, humidity, brightness, and a state of a road surface.
The vehicle-exterior information detector 141 provides data
indicating a result of the detection process to, for example, the
self-location estimator 132, a map analyzer 151, a traffic-rule
recognition section 152, and a state recognition section 153 of the
state analyzer 133, as well as an emergency-situation avoiding
section 171 of the operation controller 135.
The in-vehicle information detector 142 performs a process of
detecting in-vehicle information using data or a signal from each
component of the vehicle control system 100. For example, the
in-vehicle information detector 142 performs processes of
authenticating and recognizing a driver, a process of detecting a
state of the driver, a process of detecting a person on board, and
a process of detecting an in-vehicle environment. Examples of the
detection-target state of a driver include a physical condition, a
degree of arousal, a degree of concentration, a degree of
tiredness, and a direction of a line of sight. Examples of the
detection-target in-vehicle environment include temperature,
humidity, brightness, and odor. The in-vehicle information detector
142 provides data indicating a result of the detection process to,
for example, the state recognition section 153 of the state
analyzer 133 and the emergency-situation avoiding section 171 of
the operation controller 135.
The vehicle state detector 143 performs a process of detecting a
state of the system-installed automobile using data or a signal
from each component of the vehicle control system 100. Examples of
the detection-target state of the system-installed automobile
include a speed, acceleration, a rudder angle, the presence or
absence of something unusual and its details, a state of driving
maneuver, a position and an inclination of a power seat, a state of
a door lock, and states of other onboard devices. The vehicle state
detector 143 provides data indicating a result of the detection
process to, for example, the state recognition section 153 of the
state analyzer 133 and the emergency-situation avoiding section 171
of the operation controller 135.
The self-location estimator 132 performs a process of estimating,
for example, the location and the pose of the system-installed
automobile using data or a signal from the respective components of
the vehicle control system 100, such as the vehicle-exterior
information detector 141, and the state recognition section 153 of
the state analyzer 133. Further, the self-location estimator 132
generates, as necessary, a local map used to estimate a
self-location (hereinafter referred to as a self-location
estimation map). The self-location estimation map is a
high-precision map that uses a technology such as simultaneous
localization and mapping (SLAM). The self-location estimator 132
provides data indicating a result of the estimation process to, for
example, the map analyzer 151, the traffic-rule recognition section
152, and the state recognition section 153 of the state analyzer
133. Further, the self-location estimator 132 stores the
self-location estimation map in the storage 111.
The state analyzer 133 performs a process of analyzing states of
the system-installed automobile and its surroundings. The state
analyzer 133 includes the map analyzer 151, the traffic-rule
recognition section 152, the state recognition section 153, and a
state prediction section 154.
The map analyzer 151 performs a process of analyzing various maps
stored in the storage 111 using, as necessary, data or a signal
from the respective components of the vehicle control system 100,
such as the self-location estimator 132 and the vehicle-exterior
information detector 141, and constructs a map that includes
information necessary for a process of automatic driving. The map
analyzer 151 provides the constructed map to, for example, the
traffic-rule recognition section 152, the state recognition section
153, and the state prediction section 154, as well as a route
planning section 161, a behavior planning section 162, and an
operation planning section 163 of the planning section 134.
The traffic-rule recognition section 152 performs a process of
recognizing traffic rules around the system-installed automobile
using data or a signal from the respective components of the
vehicle control system 100, such as the self-location estimator
132, the vehicle-exterior information detector 141, and the map
analyzer 151. For example, a location and a state of a traffic
light around the system-installed automobile, the details of a
traffic control performed around the system-installed automobile,
and a travelable lane are recognized by the recognition process
being performed. The traffic-rule recognition section 152 provides
data indicating a result of the recognition process to, for
example, the state prediction section 154.
The state recognition section 153 performs a process of recognizing
a state related to the system-installed automobile using data or a
signal from the respective components of the vehicle control system
100, such as the self-location estimator 132, the vehicle-exterior
information detector 141, the in-vehicle information detector 142,
the vehicle state detector 143, and the map analyzer 151. For
example, the state recognition section 153 performs a process of
recognizing, for example, a state of the system-installed
automobile, a state of the surroundings of the system-installed
automobile, and a state of a driver of the system-installed
automobile. Further, the state recognition section 153 generates,
as necessary, a local map used to recognize a state of the
surroundings of the system-installed automobile (hereinafter
referred to as a state-recognition map). The state-recognition map
is, for example, an occupancy grid map.
Examples of the recognition-target state of the system-installed
automobile include a location, a pose, and a movement (such as a
speed, acceleration, and a movement direction) of the
system-installed automobile, as well as the presence or absence of
something unusual and its details. Examples of the
recognition-target state of the surroundings of the
system-installed automobile include the type and a location of a
stationary object around the system-installed automobile; the type,
a location, and a movement (such as a speed, acceleration, and a
movement direction) of a moving object around the system-installed
automobile; a structure of a road around the system-installed
automobile and a state of the surface of the road; and weather,
temperature, humidity, and brightness around the system-installed
automobile. Examples of the recognition-target state of a driver
include a physical condition, a degree of arousal, a degree of
concentration, a degree of tiredness, a movement of a line of
sight, and driving maneuver.
The state recognition section 153 provides data indicating a result
of the recognition process (that includes a state-recognition map
as necessary) to, for example, the self-location estimator 132 and
the state prediction section 154. Further, the state recognition
section 153 stores the state-recognition map in the storage
111.
The state prediction section 154 performs a process of predicting a
state related to the system-installed automobile using data or a
signal from the respective components of the vehicle control system
100, such as the map analyzer 151, the traffic-rule recognition
section 152, and the state recognition section 153. For example,
the state prediction section 154 performs a process of predicting,
for example, a state of the system-installed automobile, a state of
the surroundings of the system-installed automobile, and a state of
a driver.
Examples of the prediction-target state of the system-installed
automobile include the behavior of the system-installed automobile,
the occurrence of something unusual, and a travelable distance.
Examples of the prediction-target state of the surroundings of the
system-installed automobile include the behavior of a moving object
around the system-installed automobile, a change in a state of a
traffic light, and a change in environment such as weather.
Examples of the prediction-target state of a driver include the
behavior and the physical condition of a driver.
The state prediction section 154 provides data indicating a result
of the prediction process to, for example, the route planning
section 161, the behavior planning section 162, and the operation
planning section 163 of the planning section 134 together with the
data from the traffic-rule recognition section 152 and the state
recognition section 153.
The route planning section 161 plans a route to a destination using
data or a signal from the respective components of the vehicle
control system 100, such as the map analyzer 151 and the state
prediction section 154. For example, the route planning section 161
sets a route from a current location to a specified destination
using a global map. Further, for example, the route planning
section 161 changes a route as appropriate according to the states
of, for example, a traffic jam, an accident, a traffic regulation,
and a construction, as well as the physical condition of a driver.
The route planning section 161 provides data indicating the planned
route to, for example, the behavior planning section 162.
Using data or a signal from the respective components of the
vehicle control system 100, such as the map analyzer 151 and the
state prediction section 154, the behavior planning section 162
plans the behavior of the system-installed automobile in order to
travel safely on the route within the time, the route and the time
being planned by the route planning section 161. For example, the
behavior planning section 162 makes plans about, for example, a
start to move, a stop, a travel direction (such as a forward
movement, a backward movement, a left turn, a right turn, and a
change in direction), a lane for traveling, a traveling speed, and
passing. The behavior planning section 162 provides data indicating
the planned behavior of the system-installed automobile to, for
example, the operation planning section 163.
Using data or a signal from the respective components of the
vehicle control system 100, such as the map analyzer 151 and the
state prediction section 154, the operation planning section 163
plans an operation of the system-installed automobile in order to
achieve the behavior planned by the behavior planning section 162.
For example, the operation planning section 163 makes plans about,
for example, an increase in speed, a decrease in speed, and a
traveling route. The operation planning section 163 provides data
indicating the planned operation of the system-installed automobile
to, for example, a speed-increase-and-decrease controller 172 and a
direction controller 173 of the operation controller 135.
The operation controller 135 controls an operation of the
system-installed automobile. The operation controller 135 includes
the emergency-situation avoiding section 171, the
speed-increase-and-decrease controller 172, and the direction
controller 173.
Using a result of the detections performed by the vehicle-exterior
information detector 141, the in-vehicle information detector 142,
and the vehicle state detector 143, the emergency-situation
avoiding section 171 performs a process of detecting emergency
situations such as collision, contact, an entry into a dangerous
zone, something unusual in a driver, and something unusual in a
vehicle. When the emergency-situation avoiding section 171 detects
the occurrence of an emergency situation, the emergency-situation
avoiding section 171 plans an operation of the system-installed
automobile in order to avoid the emergency situation such as a
sudden stop or a quick turning. The emergency-situation avoiding
section 171 provides data indicating the planned operation of the
system-installed automobile to, for example, the
speed-increase-and-decrease controller 172 and the direction
controller 173.
The speed-increase-and-decrease controller 172 controls an increase
and a decrease in speed in order to achieve the operation of the
system-installed automobile planned by the operation planning
section 163 or the emergency-situation avoiding section 171. For
example, the speed-increase-and-decrease controller 172 calculates
a control target value for a drive force generator or a braking
device, the control target value being a value for achieving the
planned increase in speed, the planned decrease in speed, or the
planned sudden stop, and provides a control instruction indicating
the calculated control target value to the driveline controller
107.
The direction controller 173 controls a direction in order to
achieve the operation of the system-installed automobile planned by
the operation planning section 163 or the emergency-situation
avoiding section 171. For example, the direction controller 173
calculates a control target value for a steering mechanism, the
control target value being a value for achieving the traveling
route planned by the operation planning section 163 or the quick
turning planned by the emergency-situation avoiding section 171,
and provides a control instruction indicating the calculated
control target value to the driveline controller 107.
3. Sequence of Process Performed by Vehicle Traveling Control
Device
Next, a sequence of a process performed by the vehicle traveling
control device is described with reference to the flowchart of FIG.
7.
FIG. 7 is a flowchart of the sequence of the process performed by
the vehicle traveling control device. Note that, for example, a
process in accordance with the flow illustrated in FIG. 7 is
performed under the control of a controller (a data processing
section) that includes, for example, a CPU that includes a function
to execute a program in accordance with a program stored in the
storage of the vehicle traveling control device.
Note that the flow described below is a process when the vehicle
traveling control device 100 illustrated in FIG. 6 is applied.
This is an example of a process including performing automatic
driving in an automatic driving mode, and further displaying
recommended-route information on a display section.
The processes of respective steps illustrated in the flowchart are
sequentially described below.
(Step S101)
First, in Step S101, the detector 131 of the automatic driving
controller 112 acquires image-capturing information regarding a
visible light camera.
This process is performed by the vehicle-exterior information
detector 141 included in the detector 131 of the automatic driving
controller 112 of the vehicle traveling control device 100
illustrated in FIG. 6.
The vehicle-exterior information detector 141 acquires an image of
a region situated in a travel direction of a vehicle, the image
being captured by a visible light camera included in the data
acquisition section 102.
For example, the captured image illustrated in FIG. 8 is
acquired.
As illustrated in FIG. 8, this captured image is displayed on a
display section (a display) 201 that is included in the output
section 106, and a user (a driver) can perform observation.
The image illustrated in FIG. 8 as an example is an image
indicating a state in which a vehicle (a system-installed vehicle)
that a user (a driver) is driving, is traveling in a left lane out
of the two lanes, there is a puddle 211 in front of the vehicle,
and another vehicle is traveling in a right lane.
(Step S102)
Next, in Step S102, the vehicle-exterior information detector 141
extracts a road-surface region from the image of the region
situated in the travel direction of a vehicle, the image being
captured by the visible light camera.
Note that, for example, the method disclosed in Non-Patent Document
1 [http://www.vision.cs.chubu.ac.jp/MPRG/f_group/f133_mis
hina2013.pdf] is used as a method for extracting a road-surface
region from an image.
Non-Patent Document 1 described above discloses a method for
extracting a road-surface region from a visible light image using
machine learning, and the road-surface region is extracted using
such a method.
(Step S103)
Next, in Step S103, a candidate course is detected.
This process is performed by the state recognition section 153 of
the automatic driving controller 112.
The state recognition section 153 sets a candidate travelable
course from the road-surface region extracted in Step S102.
Note that, in the process of detecting a candidate course,
information such as information regarding a self-location of a
vehicle, traveling speed information (a vehicle state), and
information regarding an obstacle around a vehicle
(vehicle-exterior information) is input, and a plurality of safely
travelable courses are determined considering the input
information, the safely travelable course being a course that is
travelable in the extracted road-surface region and in which there
is no sharp change in course from a current traveling state.
Note that the information regarding a self-location of a vehicle is
input from the self-location estimator 132. Further, the traveling
speed information (the vehicle state) is input from the vehicle
state detector 143. Furthermore, the information regarding an
obstacle around a vehicle (the vehicle-exterior information) is
input from the vehicle-exterior information detector 141.
Considering the pieces of information input by these respective
processing sections, the state recognition section 153 sets a
plurality of candidate courses that are travelable and in which
there is no sharp change in course from a current traveling
state.
For example, as illustrated in FIG. 9, three routes (routes a, b,
and c) are detected as candidate courses.
As illustrated in FIG. 9, the candidate-course (route) information
is displayed on the display section (the display) 201 included in
the output section 106, and a user (a driver) can confirm the
information.
(Step S104)
Next, in Step S104, information regarding a road-surface
temperature on the candidate course detected in Step S103 is
analyzed using an image acquired by a (far-)infrared camera.
This process is performed by the vehicle-exterior information
detector 141 of the detector 131.
The vehicle-exterior information detector 141 acquires an image of
a road surface in a travel direction of a vehicle, the image being
captured by the (far-)infrared camera included in the data
acquisition section 102, and analyzes a road-surface temperature on
each of the candidate courses using a pixel value of the acquired
far-infrared image.
As described above, the far-infrared image is, for example, a
light-and-shade image depending on a temperature distribution.
Specifically, it is acquired as a monochrome image that becomes
whiter with a higher temperature, in which, for example, a
high-temperature portion is represented in white and a
low-temperature portion is represented in black. The
vehicle-exterior information detector 141 analyzes a road-surface
temperature on each of the candidate courses using a pixel value of
such a far-infrared image.
A result of the analysis is input to the state recognition section
153.
Further, the analysis result is displayed on the display section
(the display) 201 included in the output section 106, and a user (a
driver) can confirm the analysis result.
For example, as illustrated in FIG. 10, the information regarding a
road-surface temperature is displayed on the display section (the
display) 201.
In the example illustrated in FIG. 10, a portion in which the
puddle 211 exists is a low-temperature region, a region of a while
line indicating a lane marking is also a low-temperature region,
and the right lane is a high-temperature region.
Note that it is favorable that an output color depending on a
temperature be set to perform display on the display section
201.
For example, as illustrated in FIG. 10, the high-temperature region
is output in a red-color setting, and the low-temperature region is
output in a green-color setting.
Such color-coding upon performing outputting enables a user (a
driver) to immediately know a road-surface temperature for each
region.
(Step S105)
The process of Step S105 is performed by the state recognition
section 153.
The state recognition section 153 inputs the information regarding
a road-surface temperature on each of the candidate courses that is
acquired by the vehicle-exterior information detector 141 in Step
S104, and, using the input information regarding a road-surface
temperature on each of the candidate courses, the state recognition
section 153 calculates an average value of a road-surface
temperature on each of the candidate course.
For example, an average value of a temperature of a road surface
having an area of about (vehicle width+2 m on its both
sides).times.(travel direction of 30 m to 100 m) is calculated for
each candidate course.
The state recognition section 153 inputs the calculated average
value of a road-surface temperature on each of the candidate
courses to the state prediction section 154.
A specific example of the process of Step S105 is described.
For example, as illustrated in FIG. 9, when three routes (the
routes a, b, and c) are detected as candidate courses, an average
value of a temperature of a road surface having an area of about
(vehicle width+2 m on its both sides).times.(travel direction of 30
m to 100 m) is calculated for each of the routes a, b, and c.
Note that the area used to calculate an average temperature
described above is a mere example, and it is favorable that a
region for which an average temperature is to be calculated be
determined considering, for example, a vehicle speed and a region
for which a road-surface temperature is to be detected.
(Step S106)
The process of Step S106 is also performed by the state recognition
section 153.
In Step S106, it is determined whether the calculation of an
average road-surface temperature in Step S105 has been completed
with respect to all of the candidate courses extracted in Step
S103.
When the calculation of an average road-surface temperature has not
been completed with respect to all of the candidate courses, the
process returns to Step S105 and the process of calculating an
average road-surface temperature is performed with respect to an
unprocessed candidate course.
When the calculation of an average road-surface temperature has
been completed with respect to all of the candidate courses, the
process moves on to Step S107.
(Step S107)
The process of Step S107 is performed by the state prediction
section 154.
Finally, in Step S107, the state prediction section 154 determines,
to be a traveling course, a candidate course in which the
temperature on the course has a largest average value. The
determined traveling course is reported to the planning section
134, and a control of a vehicle is finally performed.
Specifically, a traveling control is performed such that the
vehicle travels along the determined course.
In other words, the planning section 134 outputs, to the operation
controller 135 that performs automatic driving of a vehicle,
control data that causes the vehicle to travel along a course of a
highest road-surface temperature.
The operation controller 135 controls an operation of the vehicle
to cause the vehicle to travel along the course of a highest
road-surface temperature.
Note that information regarding the determined traveling course
(route) is displayed on the display section (the display) 201
included in the output section 106, as illustrated in FIG. 11, and
a user (a driver) can confirm the information.
FIG. 11 illustrates an example of selecting the route b from among
the routes a to c illustrated in FIG. 9.
As can be seen from the distribution of a temperature on each
candidate course illustrated in FIG. 10, the route b is a route in
which a vehicle travels in a region of a highest road-surface
temperature.
The selection of such a traveling route makes it possible to travel
in a portion of a high road-surface temperature, which results in
being able to reduce a rolling resistance of a tire and to travel
with improved fuel efficiency.
Note that the process in accordance with the flow illustrated in
FIG. 7 is continuously performed repeatedly when a vehicle is
traveling.
By continuously performing the process above, it becomes possible
to travel while continuously selecting a region of a high
road-surface temperature, which results in achieving an improvement
in fuel efficiency when a vehicle is traveling.
The road-surface temperature varies depending on, for example, a
road-surface state (such as a material of a pavement, and wet and
dry) and whether there exists a vehicle ahead. For example, when
there is a puddle on a course, such a portion with a puddle
generally has a temperature lower than the surroundings of the
portion.
The application of the configuration of the present disclosure
makes it possible to select a course that permits avoidance of
puddle, and this results in being able to improve fuel efficiency.
Further, for example, when the pavement material of a portion of a
road surface is different from that of the other portion, the
road-surface temperature differs depending on a pavement material.
For example, the road-surface temperature is low with respect to a
white line. The application of the configuration of the present
disclosure makes it possible to travel while avoiding such a region
of a low road-surface temperature and selecting a road surface of a
higher temperature, and this results in being able to improve fuel
efficiency.
Further, for example, it is known that, when there exists a vehicle
traveling ahead, the road-surface temperature varies to become
higher due to heat from the vehicle (such as a frictional heat from
a tire, a radiant heat from a vehicle, and a sensible heat induced
due to a passage of a vehicle). The application of the
configuration of the present disclosure makes it possible to
select, when there exists a vehicle traveling ahead, a route that
follows this vehicle, and this results in being able to travel with
improved fuel efficiency.
As described above, the vehicle traveling control device of the
present disclosure makes it possible to continuously measure a
temperature of a road surface in a travel direction when a vehicle
is traveling, to set a traveling route such that a region of a high
road-surface temperature is selected, and to cause a vehicle to
travel along the set route, and this results in being able to
improve fuel efficiency with certainty.
Note that, in the embodiments described above, an example in which
average values of a road-surface temperature of respective
candidate courses are calculated as evaluation values for the
respective candidate courses, and the calculated average values are
compared, has been described, but, for example, maximum values or
median values of a road-surface temperature of the respective
candidate courses may be used as evaluation values.
4. Summary of Configuration of Present Disclosure
The embodiments of the present disclosure have been described above
in details with reference to the specific embodiment. However, it
is clear that those skilled in the art could make modifications or
alterations thereto without departing from the scope of the present
disclosure. In other words, the present disclosure has been
described illustratively, and should not be restrictively
interpreted. The claims should be considered in order to determine
the scope of the present disclosure.
Note that the technology disclosed herein may take the following
configurations.
(1) A vehicle traveling control device including:
a detector that analyzes an image captured by a far-infrared camera
to analyze a distribution of a road-surface temperature; and
a state analyzer that determines a course of a highest road-surface
temperature to be a traveling route, using the distribution of a
road-surface temperature.
(2) The vehicle traveling control device according to (1), further
including
a planning section that outputs control data to an operation
controller that performs automatic driving of a vehicle, the
control data being data for causing the vehicle to travel along the
course of the highest road-surface temperature.
(3) The vehicle traveling control device according to (1) or (2),
in which
the state analyzer detects a candidate course travelable for a
vehicle, the state analyzer detecting a plurality of the candidate
courses, calculates an average value of a road-surface temperature
of each of the plurality of the candidate courses, and determines,
to be a traveling route, the candidate course having a largest
average value of a road-surface temperature.
(4) The vehicle traveling control device according to (1) or (2),
in which
the state analyzer detects a candidate course travelable for a
vehicle, the state analyzer detecting a plurality of the candidate
courses, calculates a maximum value or a median value of a
road-surface temperature of each of the plurality of the candidate
courses, and determines, to be a traveling route, the candidate
course having a largest maximum value or a largest median value of
a road-surface temperature.
(5) The vehicle traveling control device according to (3) or (4),
in which
the state analyzer inputs at least one of information regarding a
self-location of a vehicle, traveling speed information, or
information regarding an obstacle around the vehicle, and detects,
as the candidate course, a course determined to be safely
travelable according to the input information.
(6) The vehicle traveling control device according to any one of
(1) to (5), in which
the detector extracts a road-surface region from an image of a
region situated in a travel direction of a vehicle, the image being
captured by a visible light camera, and analyzes a distribution of
a temperature of a road surface included in the extracted
road-surface region.
(7) The vehicle traveling control device according to any one of
(1) to (6), further including
a display section that displays direction information regarding the
course of the highest road-surface temperature.
(8) The vehicle traveling control device according to (7), in
which
the display section displays information indicating a temperature
distribution of a road-surface temperature.
(9) The vehicle traveling control device according to (8), in
which
the display section displays, as the information indicating a
temperature distribution of a road-surface temperature, information
in which an output color depending on a temperature is set.
(10) A vehicle traveling control method that is performed in a
vehicle traveling control device, the method including
performing, by a detector, detection including analyzing an image
captured by a far-infrared camera to analyze a distribution of a
road-surface temperature; and
performing, by a state analyzer, a state analysis including
determining a course of a highest road-surface temperature to be a
traveling route, using the distribution of a road-surface
temperature.
(11) A program that causes a vehicle traveling control device to
perform a vehicle traveling control, the vehicle traveling control
including:
performing detection including causing a detector to analyze an
image captured by a far-infrared camera to analyze a distribution
of a road-surface temperature; and
performing a state analysis including causing a state analyzer to
determine a course of a highest road-surface temperature to be a
traveling route, using the distribution of a road-surface
temperature.
Further, a series of processes described herein can be performed
using hardware or software or a combination of them. When a process
performed using software is performed, a program in which a
processing sequence is recorded can be installed on a memory to be
executed, the memory being in a computer incorporated in dedicated
hardware, or the program can be installed on a general-purpose
computer to be executed, the general-purpose computer being capable
of performing various processes. For example, the program can be
recorded in a recording medium in advance. In addition to
installing the program on a computer from a recording medium, the
program can be received through a network such as a local area
network (LAN) or the Internet to be installed on a recording medium
such as a built-in hard disk.
Note that the various processes described herein are not limited to
being chronologically performed in the description order, and they
may be performed in parallel or individually according to the
capability of a device that performs the processes, or as
necessary. Further, a system herein is a logical collection of a
plurality of devices, and is not limited to having a configuration
in which each included device is situated in a single housing.
INDUSTRIAL APPLICABILITY
As described above, the configuration of the embodiment of the
present disclosure makes it possible to travel while detecting a
road-surface temperature and selecting a region of a high
road-surface temperature, and thus to travel with improved fuel
efficiency.
Specifically, for example, an image captured by a far-infrared
camera is analyzed to analyze a distribution of a road-surface
temperature, and a course of a highest road-surface temperature is
determined to be a traveling route. Further, automatic driving
along the course of the highest road-surface temperature is
performed. Furthermore, a state of the distribution of a
road-surface temperature, and a direction of the course of the
highest road-surface temperature are displayed on a display
section, so that a user (a driver) recognizes them. For example, a
state analyzer detects a candidate course travelable for a vehicle,
the state analyzer detecting a plurality of the candidate courses,
calculates an average value of a road-surface temperature of each
of the plurality of the candidate courses, and determines the
candidate course having a largest average value of a road-surface
temperature to be a traveling route.
This configuration makes it possible to travel while detecting a
road-surface temperature and selecting a region of a high
road-surface temperature, and thus to travel with improved fuel
efficiency.
REFERENCE SIGNS LIST
10 automobile
20 far-infrared camera
30 visible light image
40 far-infrared image
50 display section
52 recommended-route information
100 vehicle traveling control device
101 input section
102 data acquisition section
103 communication section
104 in-vehicle device
105 output controller
106 output section
107 driveline controller
108 driveline system
109 body-related controller
110 body-related system
111 storage
112 automatic driving controller p 131 detector
132 self-location estimator
133 state analyzer
134 planning section
135 operation controller
141 vehicle-exterior information detector
142 in-vehicle information detector
143 vehicle state detector
151 map analyzer
152 traffic-rule recognition section
153 state recognition section
154 state prediction section
161 route planning section
162 behavior planning section
163 operation planning section
171 emergency-situation avoiding section
172 speed-increase-and-decrease controller
173 direction controller
201 display section
* * * * *
References